Green Trace: Secure and Traceable Food Security System Based on Blockchain and Domain Ontology

Ensuring food quality and safety is now crucial due to the increasing occurrence of various cyberattacks and fraud in vulnerable environments. Blockchain technology offers one of the most promising solutions through private data sharing and integrity to revolutionize supply chain processes. In this paper, blockchain and domain ontology capabilities are employed to develop a secure and traceable supply chain management system called Green Trace. Green Trace incorporates multiple participants, including the sender, receiver, food fraud detection agent, and wallet. The food fraud detection mechanism utilizes semantic reasoning rules to significantly enhance fraud detection efficiency and precision. We assess the Green Trace system's performance by conducting a real-time case study in Algeria focusing on food fraud detection. The ontology rules and a smart contract result in a 70% reduction in food fraud due to efficient semantic indexing and reuse of inference effects. This advancement signifies an unprecedented innovation in blockchain-based supply chain management. Moreover, in terms of retrieval time, the Green Trace system outperforms traditional iterative search and secure techniques, offering the most efficient retrieval time.